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We study the numerical approximation of numerous processes, solutions of nonlinear stochastic differential equations, that appear in various applications such as financial mathematics and population dynamics. Between the investigated models…

Numerical Analysis · Mathematics 2021-04-14 N. Halidias , I. S. Stamatiou

We consider the explicit numerical approximations of stochastic differential equations (SDEs) driven by Brownian process and Poisson jump. It is well known that under non-global Lipschitz condition, Euler Explicit method fails to converge…

Numerical Analysis · Mathematics 2018-02-21 Antoine Tambue , Jean Daniel Mukam

We describe a mesh-free three-dimensional numerical scheme for solving the incompressible semi-geostrophic equations based on semi-discrete optimal transport techniques. These results generalise previous two-dimensional implementations. The…

Numerical Analysis · Mathematics 2026-02-12 Théo Lavier

The 2D Euler equations are a simple but rich set of non-linear PDEs that describe the evolution of an ideal inviscid fluid, for which one dimension is negligible. Solving numerically these equations can be extremely demanding. Several…

Numerical Analysis · Mathematics 2023-01-18 Paolo Cifani , Sagy Ephrati , Milo Viviani

This paper investigates the strong convergence properties of two Euler-type methods for a class of time-changed stochastic differential equations (TCSDEs) with super-linearly growing drift and diffusion coefficients. Building upon existing…

Numerical Analysis · Mathematics 2026-01-16 Shuai Wang , Yuanling Niu , Ying Zhang

In this paper, we present a numerical scheme to solve the initial-boundary value problem for backward stochastic partial differential equations of parabolic type. Based on the Galerkin method, we approximate the original equation by a…

Optimization and Control · Mathematics 2015-07-16 Yanqing Wang

This paper deals with the numerical approximation of semilinear parabolic stochastic partial differential equation (SPDE) driven simultaneously by Gaussian noise and Poisson random measure, more realistic in modeling real world phenomena.…

Numerical Analysis · Mathematics 2020-11-19 Jean Daniel Mukam , Antoine Tambue

In this article, we prove the convergence of a semi-discrete numerical method applied to a general class of nonlocal nonlinear wave equations where the nonlocality is introduced through the convolution operator in space. The most important…

Numerical Analysis · Mathematics 2020-08-04 H. A. Erbay , S. Erbay , A. Erkip

In this article, we addressed the numerical solution of a non-linear evolutionary variational inequality, which is encountered in the investigation of quasi-static contact problems. Our study encompasses both the semi-discrete and…

Numerical Analysis · Mathematics 2024-01-05 Kamana Porwal , Tanvi Wadhawan

In this manuscript, we propose efficient stochastic semi-explicit symplectic schemes tailored for nonseparable stochastic Hamiltonian systems (SHSs). These semi-explicit symplectic schemes are constructed by introducing augmented…

Numerical Analysis · Mathematics 2024-05-24 Jialin Hong , Baohui Hou , Liying Sun

Explicit numerical finite difference schemes for partial differential equations are well known to be easy to implement but they are particularly problematic for solving equations whose solutions admit shocks, blowups and discontinuities.…

Numerical Analysis · Mathematics 2016-10-19 Christopher. N. Angstmann , Bruce I. Henry , Byron A. Jacobs , Anna V. McGann

This paper aims to investigate the numerical approximation of semilinear non-autonomous stochastic partial differential equations (SPDEs) driven by multiplicative or additive noise. Such equations are more realistic than autonomous SPDEs…

Numerical Analysis · Mathematics 2020-11-18 Jean Daniel Mukam , Antoine Tambue

We construct a positivity-preserving Lie--Trotter splitting scheme with finite difference discretization in space for approximating the solutions to a class of nonlinear stochastic heat equations with multiplicative space-time white noise.…

Numerical Analysis · Mathematics 2023-02-20 Charles-Edouard Bréhier , David Cohen , Johan Ulander

In this paper, we propose a tensor type of discretization and optimization process for solving high dimensional partial differential equations. First, we design the tensor type of trial function for the high dimensional partial differential…

Numerical Analysis · Mathematics 2022-12-01 Yangfei Liao , Yifan Wang , Hehu Xie

In this paper, we consider scalar stochastic differential equations (SDEs) with a superlinearly growing and piecewise continuous drift coefficient. Existence and uniqueness of strong solutions of such SDEs are obtained. Furthermore, the…

Probability · Mathematics 2022-06-02 Huimin Hu , Siqing Gan

We consider the stochastic Allen--Cahn equation perturbed by smooth additive Gaussian noise in a spatial domain with smooth boundary in dimension $d\le 3$, and study the semidiscretisation in time of the equation by an Euler type split-step…

Numerical Analysis · Mathematics 2018-04-27 Mihály Kovács , Stig Larsson , Fredrik Lindgren

Higher order schemes for stochastic partial differential equations that do not possess commutative noise require the simulation of iterated stochastic integrals. In this work, we propose a derivative-free Milstein type scheme to approximate…

Probability · Mathematics 2020-06-16 Claudine von Hallern , Andreas Rößler

In this work, we concern with the high order numerical methods for coupled forward-backward stochastic differential equations (FBSDEs). Based on the FBSDEs theory, we derive two reference ordinary differential equations (ODEs) from the…

Numerical Analysis · Mathematics 2014-03-27 Weidong Zhao , Yu Fu , Tao Zhou

In order to inherit numerically the ergodicity of the damped stochastic nonlinear Schr\"odinger equation with additive noise, we propose a fully discrete scheme, whose spatial direction is based on spectral Galerkin method and temporal…

Numerical Analysis · Mathematics 2016-06-07 Chuchu Chen , Jialin Hong , Xu Wang

In this article we introduce several kinds of easily implementable explicit schemes, which are amenable to Khasminski's techniques and are particularly suitable for highly nonlinear stochastic differential equations (SDEs). We show that…

Numerical Analysis · Mathematics 2020-02-18 Xiaoyue Li , Xuerong Mao , Hongfu Yang